Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST.

ABSTRACT: Spatially resolved transcriptomics involves a set of emerging technologies that enable the transcriptomic profiling of tissues with the physical location of expressions. Although a variety of methods have been developed for data integration, most of them are for single-cell RNA-seq datasets without consideration of spatial information. Thus, methods that can integrate spatial transcriptomics data from multiple tissue slides, possibly from multiple individuals, are needed. Here, we present PRECAST, a data integration method for multiple spatial transcriptomics datasets with complex batch effects and/or biological effects between slides. PRECAST unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, while requiring only partially shared cell/domain cl

SUBMITTER: Liu W 

PROVIDER: S-EPMC9849443 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature